code: def performOneTest(
      frameWithNA,
      frameWithoutNA,
      interactionColumn,
      xcols,
      standard=True,
  ):
      # default missing value handling = meanImputation
      h2o_df_NA = h2o.H2OFrame(frameWithNA, na_strings=["UNKNOWN"])
      h2o_df_NA_Valid = h2o.H2OFrame(
          frameWithNA, na_strings=["UNKNOWN"]
      )
      h2o_df = h2o.H2OFrame(frameWithoutNA, na_strings=["UNKNOWN"])
      h2o_df_valid = h2o.H2OFrame(
          frameWithoutNA, na_strings=["UNKNOWN"]
      )
      # build model with and without NA in Frame
      modelNA = H2OGeneralizedLinearEstimator(
          family="Binomial",
          alpha=0,
          lambda_search=False,
          interactions=interactionColumn,
          standardize=standard,
      )
      modelNA.train(
          x=xcols,
          y="label",
          training_frame=h2o_df_NA,
          validation_frame=h2o_df_NA_Valid,
      )
      model = H2OGeneralizedLinearEstimator(
          family="Binomial",
          alpha=0,
          lambda_search=False,
          interactions=interactionColumn,
          standardize=standard,
      )
      model.train(
          x=xcols,
          y="label",
          training_frame=h2o_df,
          validation_frame=h2o_df_valid,
      )
      # extract GLM coefficients
      coef_m_NA = modelNA._model_json["output"]["coefficients_table"]
      coef_m = model._model_json["output"]["coefficients_table"]
  
      if not (
          len(coef_m_NA.cell_values) == len(coef_m.cell_values)
      ):  # deal with 0 coeff for NA
          assert_arrays_equal_NA(
              coef_m_NA.cell_values, coef_m.cell_values
          )
      else:
          pyunit_utils.equal_2d_tables(
              coef_m_NA.cell_values, coef_m.cell_values
          )
  
file_path: h2o-3/h2o-py/tests/testdir_algos/glm/pyunit_pubdev_6999_glm_interaction_NA.py
imports: from past.utils import old_div
  import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
  import pandas
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: performOneTest(frameWithNA, frameWithoutNA, interactionColumn, xcols, standard) without return types